Protein structural data have long been presented in computer processable form. This project will develop a system for manipulating not only the chemical data, but the knowledge or hypotheses about biochemical structure that may be proposed by researchers. Using techniques of artificial intelligence, protein sequences will be interpreted to infer more complex structures under the guidance of experts who may propose and test hypotheses interactively using a computer system. Protein structural knowledge will be represented in a hierarchy of units that may be manipulated by rules either derived from existing methods of structure interpretation or from new hypotheses developed while using the system. Feedback about the application of combinations of those rules to know structures will be generated to suggest improvements in hypotheses. Application of these types of knowledge representation and of protein structural predictions, in particular, are widespread in basic medical research, drug design and cancer therapy planning.